Connectivism is the application of network principles to define both knowledge and the process of learning. Knowledge is defined as a particular pattern of relationships and learning is defined as the creation of new connections and patterns as well as the ability to maneuver around existing networks/patterns.

<span class="blsp-spelling-error" id="SPELLING_ERROR_30">Kirshner</span> argues, very clearly, that non-<span class="blsp-spelling-error" id="SPELLING_ERROR_31">instructivist</span> methods result in no better learning than direct instruction, and sometimes in *less* learning, because of the 'cognitive overhead' required in self-directed methodologies.<br><br><span class="blsp-spelling-error" id="SPELLING_ERROR_32">Kirshner's</span> argument on this point is not based on experimental data, but rather, on his theory of cognition. Specifically, he argues that short-term memory has a limited capacity, and that if some of this capacity is not available for new facts (because it is taken up 'selecting scientific principles') then the transfer of information to the student is reduced.<br><br>I respond to <span class="blsp-spelling-error" id="SPELLING_ERROR_33">this</span> argument by showing how <span class="blsp-spelling-error" id="SPELLING_ERROR_34">Kirshner's</span> theory is false. We do not 'retrieve theories' into short term memory and then 'select' from them. That is not how thinking works; that is not ow scientific thinking works. And therefore, <span class="blsp-spelling-error" id="SPELLING_ERROR_35">Kirshner's</span> argument, on these grounds, against student-directed learning, fails.

The best mechanism for demonstrating knowledge is not likely the production of a certain set of facts on demand. Expertise in a discipline on the <span class="blsp-spelling-error" id="SPELLING_ERROR_54">part</span> of a student is something that is typically *recognized*, not measured, by people who are already experts in the field.